BINSREG

The binsreg package provides tools for statistical analysis using the binscatter methods.

• binsreg: implements binscatter least squares regression with robust inference and plots, including curve estimation, pointwise confidence intervals and uniform confidence band.
• binsqreg: implements binscatter quantile regression with robust inference and plots, including curve estimation, pointwise confidence intervals and uniform confidence band.
• binsglm: implements binscatter generalized linear regression with robust inference and plots, including curve estimation, pointwise confidence intervals and uniform confidence band.
• binstest: implements binscatter-based hypothesis testing procedures for parametric specifications of and shape restrictions on the unknown function of interest.
• binspwc: implements hypothesis testing procedures for pairwise group comparison of binscatter estimators.
• binsregselect: implements data-driven number of bins selectors for binscatter implementation using either quantile-spaced or evenly-spaced binning/partitioning.

All the commands allow for covariate adjustment, smoothness restrictions, and clustering, among other features. See Cattaneo, Crump, Farrell and Feng (2024, 2025, 2026) for references.

Website: https://nppackages.github.io/.

Source code: https://github.com/nppackages/binsreg.

Authors

Matias D. Cattaneo (matias.d.cattaneo@gmail.com)

Richard K. Crump (richard.crump@gmail.com)

Max H. Farrell (mhfarrell@gmail.com)

Yingjie Feng (fengyingjiepku@gmail.com)

Ricardo Masini (ricardo.masini@gmail.com)

Installation

To install/update use pip

pip install binsreg

Usage

from binsreg import binsregselect, binsreg, binsqreg, binsglm, binstest, binspwc

• Replication: binsreg illustration, plot illustration, simulated data.

Dependencies

• numpy
• pandas
• scipy
• statsmodels
• plotnine

References

For overviews and introductions, see NP Packages website.

Software and Implementation

• Cattaneo, Crump, Farrell and Feng (2025): Binscatter Regressions.
  Stata Journal 25(1): 3-50.

Technical and Methodological

• Cattaneo, Crump, Farrell and Feng (2024): On Binscatter.
  American Economic Review 114(5): 1488-1514.
  Supplemental Appendix

• Cattaneo, Crump, Farrell and Feng (2026): Nonlinear Binscatter Methods.
  Review of Economics and Statistics, revise and resubmit.
  Supplemental Appendix